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5032722 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
ABOUT:
=======
preprocess pfam data
"""
import sys
import argparse
import subprocess
from initial_cleaning.initial_cleaning import main as initial_cleaning_fn
from prepare_for_featurization.prepare_for_featurization import main as split_n_pick
from generate_inputs.make_features import main as make_features
from generate_inputs.precalculate_counts_for_pairHMM import precalculate_counts_for_pairHMM
from concatenate_parts.concatenate_parts import main as concat_parts
from utils.utils import make_sub_folder
def main():
parser = argparse.ArgumentParser(
prog='data_preproc',
description='Preprocess data into cherries')
parser.add_argument('-pfam_seed_file',
required=True,
type = str,
help = '(str) Name of the original single seed file; if in a folder, provide the path too')
parser.add_argument('-tree_dir',
required=True,
type = str,
help = '(str) the folder of .tree files from PFam+FastTree; if in a folder, provide the path too')
parser.add_argument('-num_splits',
type = int,
default = 10,
help = '(int) number of splits (not including OOD valid)')
parser.add_argument('-metadata_header',
type = str,
default = 'metadata',
help = '(str) Header to add to output stats file')
parser.add_argument('-rand_key',
type = int,
default = 6,
help = '(int) random key for randomly selecting data splits')
parser.add_argument('-topk1_valid',
type = int,
default = 3,
help = '(int) number of widest pfams for OOD valid')
parser.add_argument('-topk2_valid',
type = int,
default = 8,
help = '(int) number of gappiest pfams for OOD valid')
parser.add_argument('-alphabet_size',
type=int,
default=20,
help ='(int) base alphabet size; 20 for amino acids')
parser.add_argument('-max_len',
type=int,
default=5000,
help ='(int) maximum length to pad all inputs to')
parser.add_argument('-batch_size',
type=int,
default=1000,
help ='(int) when precalculating event counts, whats the batch size to do so')
args = parser.parse_args()
# 1.) clean
initial_cleaning_fn(pfam_seed_file = args.pfam_seed_file,
tree_dir = args.tree_dir,
header = args.metadata_header)
# 2.) split into cherries
split_n_pick(pfam_seed_file = args.pfam_seed_file,
tree_dir = args.tree_dir,
num_splits = args.num_splits,
rand_key = args.rand_key,
topk1_valid = args.topk1_valid,
topk2_valid = args.topk2_valid)
# 3.) make features (not including summary counts)
cherries_folder = 'CHERRIES-FROM_' + args.tree_dir.replace('/trees','')
make_features(num_splits = args.num_splits,
max_len = args.max_len,
seed_folder = 'seed_alignments',
trees_folder = args.tree_dir,
cherries_folder = cherries_folder)
# 4.) precalculate counts; this can be slow
precalculate_counts_for_pairHMM(splitname = 'CHERRIES_valid',
batch_size = args.batch_size)
for i in range(args.num_splits):
precalculate_counts_for_pairHMM(splitname = f'CHERRIES_split{i}',
batch_size = args.batch_size)
# 5.) concatenate everything (per folder)
concat_parts(splitname = 'CHERRIES_valid',
alphabet_size = args.alphabet_size)
for i in range(args.num_splits):
concat_parts(splitname = f'CHERRIES_split{i}',
alphabet_size = args.alphabet_size)
# 6.) clean up
subprocess.run(["bash", "tear_down.sh"], check=True)
if __name__ == '__main__':
main()
# # example inputs
# args.pfam_seed_file = 'EXAMPLE_INPUTS/EXAMPLE_Pfam-A.seed'
# args.tree_dir = 'EXAMPLE_INPUTS/trees'
# args.num_splits = 2
# args.metadata_header = 'header'
# args.rand_key = 42
# args.topk1_valid = 0
# args.topk2_valid = 0
# args.alphabet_size = 20
# args.max_len = 5000
# args.batch_size = 10
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